Materializations strategy in dbt - Step-by-Step Execution

Concept Flow - Materializations strategy

Start: Define model

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Choose materialization type

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Table

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Create physical table

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View

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Create virtual view

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Incremental

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Append or update data

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Ephemeral

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Inline CTE in queries

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Run dbt model

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Materialization applied

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Data ready for use

This flow shows how dbt chooses a materialization strategy for a model and applies it to create tables, views, or inline queries.

Execution Sample

dbt

model.sql:
-- materialized as table
select * from source_table

-- materialized as view
{{ config(materialized='view') }}
select * from source_table

-- materialized as incremental
{{ config(materialized='incremental') }}
select * from source_table

-- materialized as ephemeral
{{ config(materialized='ephemeral') }}
select * from source_table

This code shows four dbt models with different materialization strategies: table, view, incremental, and ephemeral.

Execution Table

Step	Model Type	Action	Result
1	table	dbt runs model.sql	Creates physical table with full data
2	view	dbt runs model.sql with view config	Creates virtual view referencing source_table
3	incremental	dbt runs model.sql with incremental config	Appends or updates only new/changed data in table
4	ephemeral	dbt runs model.sql with ephemeral config	Inlines SQL as CTE in dependent models, no table/view created
5	all	dbt finishes run	Models materialized as per config, data ready for queries

💡 All models processed with their materialization strategy; dbt run completes successfully

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	Final
model_type	undefined	table	view	incremental	ephemeral	all processed
physical_object	none	table created	view created	table updated incrementally	no object created	all materialized
data_state	source data	full data copied	virtual view points to source	partial data updated	data inlined in queries	ready for use

Key Moments - 3 Insights

Why does the ephemeral materialization not create a table or view?

Because ephemeral models are inlined as CTEs inside dependent models, no physical object is created. See execution_table row 4.

How does incremental materialization differ from table materialization?

Incremental only adds or updates new data instead of recreating the whole table, making it faster. See execution_table rows 1 and 3.

What happens if you don't specify a materialization in dbt?

By default, dbt materializes models as tables, creating a physical table with full data. See execution_table row 1.

Visual Quiz - 3 Questions

Look at the execution_table, what does dbt do at Step 2 for a view model?

A Creates a physical table with data

B Appends new data to an existing table

C Creates a virtual view referencing source_table

D Inlines SQL as a CTE in dependent models

💡 Hint

Check execution_table row 2 under 'Result' column

At which step does dbt update only new or changed data instead of recreating the whole table?

A Step 3

B Step 2

C Step 1

D Step 4

💡 Hint

Look at execution_table row 3 describing incremental materialization

If you want no physical table or view created, which materialization should you choose?

A view

B ephemeral

C incremental

D table

💡 Hint

Refer to execution_table row 4 about ephemeral materialization

Concept Snapshot

dbt Materializations:
- table: creates physical table with full data
- view: creates virtual view
- incremental: updates/appends data
- ephemeral: inlines SQL, no table/view
Choose based on performance and use case
Run dbt to apply chosen materialization

Full Transcript

This visual execution shows how dbt applies different materialization strategies to models. First, you define your model SQL and choose a materialization type: table, view, incremental, or ephemeral. When dbt runs, it creates a physical table for 'table' models, a virtual view for 'view' models, updates only new or changed data for 'incremental' models, and inlines SQL as CTEs for 'ephemeral' models without creating physical objects. Variables like model_type and physical_object change step-by-step as dbt processes each model. Key points include understanding that ephemeral models do not create tables or views, incremental models update data efficiently, and the default is table materialization if none is specified. The quizzes test your understanding of these steps and outcomes. This helps you choose the right materialization for your data workflow.